Online Quintic Path Planning of Minimum Curvature Variation with Application in Collision Avoidance
Sheng Zhu, Şükrü Yaren Gelbal, Bilin Aksun‐Güvenç · 2018
Path planning is a crucial task in automated driving. Due to the complexity of dynamically changing driving environment, the planned path generally requires the capability to adjust itself in real time to avoid obstacles detected in its way. The use of an optimization method is able to generate a collision-free and smooth path. However, its high computation burden limits its direct application to online path planning. This paper proposed a time-efficient online table-lookup approach to deal with this dilemma. Given discrete target points, this approach is capable to form a quintic-spline path with second-order geometric (G2-) continuity using a look-up table. The look-up table was generated beforehand in the reference space with minimization on curvature variation. The paper demonstrates the application of this online approach in collision avoidance, with a geometry-based method to decide new target points when obstacles are detected in the original path. These new target points are fed to the table-lookup online path planning algorithm to generate a collision-free path with minimum curvature variation.